Vesalius: high-resolution in silico anatomization of spatial transcriptomic data using image analysis
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Vesalius : high-resolution in silico anatomization of spatial transcriptomic data using image analysis. / Martin, Patrick C.N.; Kim, Hyobin; Lövkvist, Cecilia; Hong, Byung Woo; Won, Kyoung Jae.
I: Molecular Systems Biology, Bind 18, Nr. 9, e11080, 2022.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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TY - JOUR
T1 - Vesalius
T2 - high-resolution in silico anatomization of spatial transcriptomic data using image analysis
AU - Martin, Patrick C.N.
AU - Kim, Hyobin
AU - Lövkvist, Cecilia
AU - Hong, Byung Woo
AU - Won, Kyoung Jae
N1 - Publisher Copyright: © 2022 The Authors. Published under the terms of the CC BY 4.0 license.
PY - 2022
Y1 - 2022
N2 - Characterization of tissue architecture promises to deliver insights into development, cell communication, and disease. In silico spatial domain retrieval methods have been developed for spatial transcriptomics (ST) data assuming transcriptional similarity of neighboring barcodes. However, domain retrieval approaches with this assumption cannot work in complex tissues composed of multiple cell types. This task becomes especially challenging in cellular resolution ST methods. We developed Vesalius to decipher tissue anatomy from ST data by applying image processing technology. Vesalius uniquely detected territories composed of multiple cell types and successfully recovered tissue structures in high-resolution ST data including in mouse brain, embryo, liver, and colon. Utilizing this tissue architecture, Vesalius identified tissue morphology-specific gene expression and regional specific gene expression changes for astrocytes, interneuron, oligodendrocytes, and entorhinal cells in the mouse brain.
AB - Characterization of tissue architecture promises to deliver insights into development, cell communication, and disease. In silico spatial domain retrieval methods have been developed for spatial transcriptomics (ST) data assuming transcriptional similarity of neighboring barcodes. However, domain retrieval approaches with this assumption cannot work in complex tissues composed of multiple cell types. This task becomes especially challenging in cellular resolution ST methods. We developed Vesalius to decipher tissue anatomy from ST data by applying image processing technology. Vesalius uniquely detected territories composed of multiple cell types and successfully recovered tissue structures in high-resolution ST data including in mouse brain, embryo, liver, and colon. Utilizing this tissue architecture, Vesalius identified tissue morphology-specific gene expression and regional specific gene expression changes for astrocytes, interneuron, oligodendrocytes, and entorhinal cells in the mouse brain.
KW - anatomical territories
KW - spatial domains
KW - spatial transcriptomics
KW - tissue architecture
KW - tissue heterogeneity
U2 - 10.15252/msb.202211080
DO - 10.15252/msb.202211080
M3 - Journal article
C2 - 36065846
AN - SCOPUS:85137192068
VL - 18
JO - Molecular Systems Biology
JF - Molecular Systems Biology
SN - 1744-4292
IS - 9
M1 - e11080
ER -
ID: 319247180